Bibliographic record
Abstract
This study is an attempt to examine fashion elements appearing in the cover-page design of fashion magazines published in Korea and aims to find Korea#s own fashion identity in fashion styling and designing of those fashion magazines. In order to do so, the study reviewed the related literature and analyzed the issues of Vogue and Harper#s Bazaar magazines published between 2004 and 2006. The results of the study can be summarized as follows: In case of fashion photographs, the largest number of 72 sampled cover-model photographs is in approximately three-quarter cut size. For the items, most take the form of one-piece dress and feature the use of a variety of accessories. In case of dresses, most are the creations of foreign designers and famous fashion models or celebrities show up, mostly alone, as features on the cover pages. Because of the nature of fashion magazines, their primary emphasis is put on the dress among other things, but on the other hand some of those magazines have differential cover pages where the model#s face is highlighted with the look of makeup or a famous female actress stands out. However, the fashion in designing the cover pages of magazines is, rather than to show the dress itself, to create a new combination of different elements as total fashion or convey an image based on such a fashion style.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".